A company's applications store data in Amazon Aurora MySQL DB clusters. The company has separate AWS accounts for its production, test, and development environments. To test new functionality in the test environment, the company's development team requires a copy of the production database four times a day.
Which solution meets this requirement with the MOST operational efficiency?
A. Take a manual snapshot in the production account. Share the snapshot with the test account. Restore the database from the snapshot.
B. Take a manual snapshot in the production account. Export the snapshot to Amazon S3. Copy the snapshot to an S3 bucket in the test account. Restore the database from the snapshot.
C. Share the Aurora DB cluster with the test account. Create a snapshot of the production database in the test account. Restore the database from the snapshot.
D. Share the Aurora DB cluster with the test account. Create a clone of the production database in the test account.
Application developers have reported that an application is running slower as more users are added. The application database is running on an Amazon Aurora
DB cluster with an Aurora Replica. The application is written to take advantage of read scaling through reader endpoints. A database specialist looks at the performance metrics of the database and determines that, as new users were added
to the database, the primary instance CPU utilization steadily increased while the Aurora Replica CPU utilization remained steady.
How can the database specialist improve database performance while ensuring minimal downtime?
A. Modify the Aurora DB cluster to add more replicas until the overall load stabilizes. Then, reduce the number of replicas once the application meets service level objectives.
B. Modify the primary instance to a larger instance size that offers more CPU capacity.
C. Modify a replica to a larger instance size that has more CPU capacity. Then, promote the modified replica.
D. Restore the Aurora DB cluster to one that has an instance size with more CPU capacity. Then, swap the names of the old and new DB clusters.
A company with 500,000 employees needs to supply its employee list to an application used by human resources. Every 30 minutes, the data is exported using the LDAP service to load into a new Amazon DynamoDB table. The data model has a base table with Employee ID for the partition key and a global secondary index with Organization ID as the partition key.
While importing the data, a database specialist receives ProvisionedThroughputExceededException errors. After increasing the provisioned write capacity units (WCUs) to 50,000, the specialist receives the same errors. Amazon CloudWatch metrics show a consumption of 1,500 WCUs.
What should the database specialist do to address the issue?
A. Change the data model to avoid hot partitions in the global secondary index.
B. Enable auto scaling for the table to automatically increase write capacity during bulk imports.
C. Modify the table to use on-demand capacity instead of provisioned capacity.
D. Increase the number of retries on the bulk loading application.
A company is looking to move an on-premises IBM Db2 database running AIX on an IBM POWER7 server. Due to escalating support and maintenance costs, the company is exploring the option of moving the workload to an Amazon Aurora PostgreSQL DB cluster.
What is the quickest way for the company to gather data on the migration compatibility?
A. Perform a logical dump from the Db2 database and restore it to an Aurora DB cluster. Identify the gaps and compatibility of the objects migrated by comparing row counts from source and target tables.
B. Run AWS DMS from the Db2 database to an Aurora DB cluster. Identify the gaps and compatibility of the objects migrated by comparing the row counts from source and target tables.
C. Run native PostgreSQL logical replication from the Db2 database to an Aurora DB cluster to evaluate the migration compatibility.
D. Run the AWS Schema Conversion Tool (AWS SCT) from the Db2 database to an Aurora DB cluster. Create a migration assessment report to evaluate the migration compatibility.
An information management services company is storing JSON documents on premises. The company is using a MongoDB 3.6 database but wants to migrate to
AWS. The solution must be compatible, scalable, and fully managed. The solution also must result in as little downtime as possible during the migration.
Which solution meets these requirements?
A. Create an AWS Database Migration Service (AWS DMS) replication instance, a source endpoint for MongoDB, and a target endpoint of Amazon DocumentDB (with MongoDB compatibility).
B. Create an AWS Database Migration Service (AWS DMS) replication instance, a source endpoint for MongoDB, and a target endpoint of a MongoDB image that is hosted on Amazon EC2
C. Use the mongodump and mongorestore tools to migrate the data from the source MongoDB deployment to Amazon DocumentDB (with MongoDB compatibility).
D. Use the mongodump and mongorestore tools to migrate the data from the source MongoDB deployment to a MongoDB image that is hosted on Amazon EC2.
A Database Specialist modified an existing parameter group currently associated with a production Amazon RDS for SQL Server Multi-AZ DB instance. The change is associated with a static parameter type, which controls the number of user connections allowed on the most critical RDS SQL Server DB instance for the company. This change has been approved for a specific maintenance window to help minimize the impact on users.
How should the Database Specialist apply the parameter group change for the DB instance?
A. Select the option to apply the change immediately
B. Allow the preconfigured RDS maintenance window for the given DB instance to control when the change is applied
C. Apply the change manually by rebooting the DB instance during the approved maintenance window
D. Reboot the secondary Multi-AZ DB instance
A business's mission-critical production workload is being operated on a 500 GB Amazon Aurora MySQL DB cluster. A database engineer must migrate the workload without causing data loss to a new Amazon Aurora Serverless MySQL DB cluster.
Which approach will result in the LEAST amount of downtime and the LEAST amount of application impact?
A. Modify the existing DB cluster and update the Aurora configuration to Serverless.
B. Create a snapshot of the existing DB cluster and restore it to a new Aurora Serverless DB cluster.
C. Create an Aurora Serverless replica from the existing DB cluster and promote it to primary when the replica lag is minimal.
D. Replicate the data between the existing DB cluster and a new Aurora Serverless DB cluster by using AWS Database Migration Service (AWS DMS) with change data capture (CDC) enabled.
A major organization maintains a number of Amazon DB clusters. Each of these clusters is configured differently to meet certain needs. These configurations may be classified into wider groups based on the team and use case.
A database administrator wishes to streamline the process of storing and updating these settings. Additionally, the database administrator want to guarantee that changes to certain configuration categories are automatically implemented to all
instances as necessary.
Which AWS service or functionality will assist in automating and achieving this goal?
A. AWS Systems Manager Parameter Store
B. DB parameter group
C. AWS Config
D. AWS Secrets Manager
A company is going to use an Amazon Aurora PostgreSQL DB cluster for an application backend. The DB cluster contains some tables with sensitive data. A Database Specialist needs to control the access privileges at the table level. How can the Database Specialist meet these requirements?
A. Use AWS IAM database authentication and restrict access to the tables using an IAM policy.
B. Configure the rules in a NACL to restrict outbound traffic from the Aurora DB cluster.
C. Execute GRANT and REVOKE commands that restrict access to the tables containing sensitive data.
D. Define access privileges to the tables containing sensitive data in the pg_hba.conf file.
A company is using an Amazon Aurora MySQL database with Performance Insights enabled. A database specialist is checking Performance Insights and observes an alert message that starts with the following phrase: `Performance Insights is unable to collect SQL Digest statistics on new queries`
Which action will resolve this alert message?
A. Truncate the events_statements_summary_by_digest table.
B. Change the AWS Key Management Service (AWS KMS) key that is used to enable Performance Insights.
C. Set the value for the performance_schema parameter in the parameter group to 1.
D. Disable and reenable Performance Insights to be effective in the next maintenance window.
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